Skip to main content

Terminal editor and site generator for SKOS taxonomies and OWL ontologies

Project description

ster

CI codecov PyPI Python 3.11+ License: MIT Ruff

rdflib typer rich pylode

   _____ ______ ______ ____
  / ___//_  __// ____// __ \
  \__ \  / /  / __/  / /_/ /
 ___/ / / /  / /___ / _, _/
/____/ /_/  /_____//_/ |_|

  [ Breton: "Meaning" or "Sense" ]
  [  Semantic Knowledge Editor  ]

ster is a terminal tool for building and publishing semantic knowledge bases. Edit SKOS taxonomies and OWL ontologies in a full-screen TUI, explore them as interactive D3 force graphs, and publish them as linked hub sites — all from your terminal, no database required.

ster is the Breton word for meaning, with homonyms for river and star. Let it guide your semantic voyage, keeping the flow and always following your star.


What's inside

Layer What ster does
Edit Full-screen TUI for SKOS concepts and OWL classes / individuals / properties
Visualise Interactive D3 v7 force graph — colour-coded clusters, drag, zoom, filter
Publish Static site generator — one hub page per entity, neighbourhood graph, media
AI assist LLM-powered concept suggestions (online or local via Ollama)
Git Stage, commit, push without leaving the terminal
Export pyLODE HTML documentation; SPARQL query runner

Features

Interactive TUI — SKOS and OWL in one view

  • Full-screen tree browser for SKOS concept schemes and OWL class hierarchies
  • Inline concept creation, renaming, deletion, and label editing
  • Detail panel: view and edit all SKOS fields (labels, definitions, scope notes, related links…)
  • OWL layer: browse classes, named individuals, object/datatype properties, axioms
  • Visual indicator for concepts with cross-scheme mapping links
  • Fold / unfold subtrees; hidden-concept count shown
  • Scheme dashboard: completion rates, quality issues, concept counts at a glance

D3 force graph visualisation

Open any ontology or taxonomy as an interactive force graph in the browser:

  • Colour-coded node clusters per root class or top concept
  • Node types rendered distinctly: OWL classes (rectangles), individuals (ellipses), SKOS concepts (small ellipses), schemes (rounded rects)
  • Representative images embedded inside nodes when schema:image is set
  • Drag, zoom, and pin nodes; hover tooltips; highlight neighbourhoods on click
  • Lane-based hierarchical layout option for SKOS concept trees

Static site generator

Turn any ontology into a linked knowledge hub with a single command:

ster site my-ontology.ttl -o ./site

Each class, individual, and concept gets its own page with:

  • Left panel — interactive D3 neighbourhood graph, centred on the entity
  • Right panel — title, badge, representative image, description, embedded videos, external links, and related entity cards
  • Index page — full-screen D3 force graph of the entire ontology, with click-to-navigate nodes

Annotate entities with schema:image, schema:video, and schema:url in your RDF file; ster picks them up automatically and renders them inline.

AI-assisted concept creation

When adding a concept (+ key), choose between entering a name manually or letting AI suggest up to 20 ordered concept names:

  • AI Auto Suggest — the AI acts as a professional taxonomist who knows your domain. It proposes names ranked by relevance, you pick one (or ask for more), and the form is pre-filled.
  • Before generating, ster shows you the exact prompt so you can review and adjust it.
  • Supports any LLM via the llm library — including local models via Ollama.
  • Pull Ollama models directly from the ⚙ Configure AI wizard without leaving ster.
  • Copy-paste mode — no local LLM needed: ster displays the prompt, copies it to the clipboard, and you paste the model's response from any web AI (ChatGPT, Claude, Gemini…).

Multi-file workspace

  • Open several .ttl files at once and see a merged taxonomy view
  • Edits are always written to the correct source file automatically

Cross-scheme mapping

  • Add exactMatch, closeMatch, broadMatch, narrowMatch, relatedMatch links between concepts in different files
  • Remove links from the detail view — works even when the target file has been deleted
  • Both source and target files are saved and staged in git on every change

Git integration

  • Stage, commit, and push changes without leaving the terminal
  • Browse full commit history with diffs inside the TUI

HTML export

  • Generate a browsable, wiki-style HTML page from any taxonomy via pyLODE
  • One HTML file per language detected in the taxonomy
  • Sticky language-switcher bar links between language versions
  • Available from the main menu or ster export

Installation

Minimal (TUI + editing)

pip install ster

With AI features

pip install "ster[ai]"

Then configure your model from the main menu: ⚙ Configure AI. No model needed if you use copy-paste mode.

With HTML export

pip install "ster[html]"

From source

git clone https://github.com/gbelbe/ster.git
cd ster
pip install -e .           # core only
pip install -e ".[ai]"     # with AI features
pip install -e ".[html]"   # with HTML export
pip install -e ".[dev]"    # with test suite

Dependencies

Group Package Purpose
core rdflib>=7.0 RDF parsing and serialisation
core typer[all]>=0.12 CLI framework
core rich>=13.0 Terminal rendering, prompts, tables
[ai] llm>=0.19 LLM abstraction layer (online & offline models)
[html] pylode>=3.0 HTML generation from SKOS / OWL (VocPub / OntPub profiles)
[dev] pytest>=8.0 Test suite
[dev] pytest-cov>=5.0 Coverage reporting

Both llm and pylode are not installed by default. When you trigger a feature that needs them, ster will offer to install the package automatically.


Quick start

Launch the interactive editor

ster

The home screen lists all ontology and taxonomy files in the current directory. Use arrow keys to navigate the action menu, then press Enter to confirm.

       ✓  my-ontology.ttl
       ✓  products.ttl

 ▶  1  ↵  Open Tree View
    2  ⊙  Graph visualisation
    3  ⎇  Browse git history
    4  🌐 Generate site
    5  🌐 Generate webpage
    6  ⚙  Configure AI
    7  ✕  Quit

Keyboard shortcuts (TUI)

Key Action
Navigate tree / fields
Enter Expand/collapse node or open detail
+ Add concept — opens a menu: enter name manually or use AI Auto Suggest
d Delete selected concept
e Edit selected field in detail panel
m Add a mapping link to another concept
g Commit & push changes
? Help screen
q / Esc Back / quit

Generate a site

ster site my-ontology.ttl -o ./site

Open ./site/index.html in a browser to explore the full D3 force graph. Click any node to navigate to its entity page.

AI Auto Suggest

Press + on any concept or scheme, then select ✦ AI Auto Suggest:

  1. ster renders the prompt and shows it for review — edit prompts.py to customise the wording
  2. Press Enter to generate; the AI suggests up to 20 concept names ranked by relevance
  3. Navigate the list and press Enter to pick a name (pre-fills the creation form)
  4. Select Suggest more to get a fresh batch with deduplication

In copy-paste mode the prompt is displayed and copied to the clipboard; paste the model's response back and press Enter on an empty line.

Export to HTML

ster export my-taxonomy.ttl          # generates ./html/my-taxonomy_en.html …
ster export my-taxonomy.ttl -l en,fr # specific languages only
ster export my-taxonomy.ttl -o /tmp  # custom output directory

Or use the 🌐 Generate webpage option from the main menu.

Validate

ster validate my-taxonomy.ttl

Annotating entities with rich media

ster reads schema:image, schema:video, and schema:url triples and uses them in both the graph visualiser and the generated site:

@prefix schema: <https://schema.org/> .

<https://example.org/MyClass> a owl:Class ;
    rdfs:label "My Class"@en ;
    schema:image <https://upload.wikimedia.org/wikipedia/commons/thumb/.../500px-image.png> ;
    schema:video <https://www.youtube.com/watch?v=...> ;
    schema:url   <https://en.wikipedia.org/wiki/My_Class> .

Images appear as thumbnails inside D3 node circles; videos are embedded as iframes in entity pages; URLs render as link cards.


Architecture

ster/
├── model.py          — Pure dataclasses: Concept, ConceptScheme, Taxonomy, RDFClass, OWLIndividual…
├── store.py          — RDF I/O via rdflib (.ttl / .rdf / .jsonld); loads SKOS + OWL layers
├── operations.py     — All SKOS mutations (add, remove, move, relate…)
├── workspace.py      — Multi-file workspace: merged view + per-file saves
├── workspace_ops.py  — Cross-file mapping operations
├── nav.py            — Full-screen TUI (curses): tree, detail, inline edit; SKOS + OWL modes
├── nav_state.py      — Typed state machine: one dataclass per viewer mode
├── nav_logic.py      — Pure functions: tree flattening, field builders, OWL node rendering
├── cli.py            — Typer entry-points (ster, ster export, ster site…)
├── ai.py             — LLM abstraction: model routing, copy-paste mode, Ollama integration
├── prompts.py        — All AI prompt templates (string.Template)
├── html_export.py    — pyLODE HTML export + D3 site generator (index + entity pages)
├── viz.py            — Standalone D3 graph: writes HTML, opens in browser
├── owl_analysis.py   — OWL axiom analysis and statistics
├── sparql_query.py   — SPARQL query runner against the loaded taxonomy
├── git_manager.py    — Git staging, commit, push
├── git_log.py        — Git history browser (TUI)
├── handles.py        — Short handle generation from camelCase URIs
└── validator.py      — SKOS integrity checks

Each layer depends only on the layers below it, keeping every module independently testable. AI prompts live in prompts.py as plain string.Template objects — edit them freely without touching any logic.


Supported formats

Extension Format
.ttl Turtle (recommended)
.rdf / .xml RDF/XML
.jsonld / .json JSON-LD
.owl OWL/XML

Development

pip install -e ".[dev]"
pytest
pytest --cov=ster --cov-report=term-missing

CI / CD

Every push and pull request runs four parallel jobs via GitHub Actions:

Job Tool What it checks
Lint ruff Code style, import order, common bugs
Type check mypy Static type correctness
Security bandit + pip-audit SAST + known CVEs in dependencies
Tests pytest × Python 3.11 / 3.12 / 3.13 Full test suite + coverage report

Coverage is uploaded to Codecov on every run.

Run checks locally

pip install -e ".[dev]"

ruff check .            # lint
ruff format --check .   # format
mypy ster/              # types
bandit -r ster/ -c pyproject.toml   # security
pip-audit               # dependency CVEs
pytest --cov=ster       # tests + coverage

Or install the pre-commit hooks to run ruff automatically on every commit:

pip install pre-commit
pre-commit install

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ster-0.3.1.tar.gz (320.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ster-0.3.1-py3-none-any.whl (203.1 kB view details)

Uploaded Python 3

File details

Details for the file ster-0.3.1.tar.gz.

File metadata

  • Download URL: ster-0.3.1.tar.gz
  • Upload date:
  • Size: 320.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for ster-0.3.1.tar.gz
Algorithm Hash digest
SHA256 1148f0d6290a34e59c31465adf39bc435919825d400851dbffd496937b636816
MD5 fcab46b3ab9962a08f492a60e3538312
BLAKE2b-256 b4356292861b1be3bce6dfb1967ee85ab023f5414fe75aa7e07df6f8476fc9df

See more details on using hashes here.

Provenance

The following attestation bundles were made for ster-0.3.1.tar.gz:

Publisher: ci.yml on gbelbe/ster

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file ster-0.3.1-py3-none-any.whl.

File metadata

  • Download URL: ster-0.3.1-py3-none-any.whl
  • Upload date:
  • Size: 203.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for ster-0.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 bce1218bc33e73a297f73df9d51293316050b806c67a9ed66ec038cfc39384ec
MD5 281ecc8e4fa88f6518fe63eb00d7f61a
BLAKE2b-256 926079dcc1b29350b645bb2fbbb98cc3504ede9915960bd18d24f4ea60a63f0a

See more details on using hashes here.

Provenance

The following attestation bundles were made for ster-0.3.1-py3-none-any.whl:

Publisher: ci.yml on gbelbe/ster

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page